Excavator Cycle Sensing for Accurate Load and Fuel Tracking
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Solution Overview
Problem
It is challenging to accurately determine the amount of material moved and fuel consumption by excavators during operations, as operators often need to manually input information, which can be cumbersome and error-prone, distracting them from the task at hand.
Innovation Solution
An excavator system that detects operating cycles, senses load characteristics, and generates control signals based on productivity metrics, including the use of sensors to measure material movement and fuel usage, allowing for automated control and data aggregation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If operators manually input information about material movement and fuel consumption, then data can be recorded, but operator distraction increases and accuracy decreases
Solution Approach 1:
The system enables self-service by automatically tracking material movement through sensors on the bucket and measuring fuel consumption through integrated fuel level sensors, eliminating the need for manual operator input and thereby reducing distraction while improving accuracy
Solution Approach 2:
The patent replaces manual mechanical data entry with automated electronic sensing systems, including bucket sensors that detect material presence and fuel level sensors that automatically measure consumption, substituting human operation with mechanical/electronic measurement systems
2Measurement precision
If automated sensors are used to track material movement, then accuracy improves, but device complexity increases
Solution Approach 1:
The system achieves multi-functionality by using the existing excavator control system and sensor network to perform multiple tasks: tracking material movement, measuring fuel consumption, monitoring operating cycles, and generating productivity reports, thereby reducing overall system complexity through shared components
Solution Approach 2:
The patent merges the material tracking function with the existing excavator control and monitoring systems, integrating sensors and data processing into the current infrastructure rather than adding separate standalone systems, which reduces overall complexity
3Productivity
If real-time control is implemented to optimize performance, then productivity improves, but device complexity increases
Solution Approach 1:
The system implements feedback by continuously monitoring material movement data, fuel consumption, and operating cycle information, then using this data to generate real-time productivity metrics and control signals that optimize excavator performance while managing system complexity through iterative adjustment
Data Source
AI summary
An excavator operating cycle is detected, and a load sensor senses a physical characteristic of a load moved during the operating cycle. The location where the load is moved to is also sensed. An amount of material moved over a set of operating cycles is determined, and an action signal is generated to control the excavator based upon the calculated amount of material.